Industry 4.0 can be interpreted as a business discipline that has led to the automation and digitalization of business systems thanks to Internet of Тhings, Cyber Physical Systems, Cognitive computing, but also Cloud computing that is crucial to the continuous development of Industry 4.0, because Cloud-based technology connects and centralizes information essential for business, and in addition provides an open source platform that improves research for the entire industry. In order to meet customer needs, different industrial branches apply Cloud computing which allows companies to adapt more easily to ongoing technological innovations. Cloud computing with unlimited networking capabilities enables businesses to optimize their business processes and activate their applications, which provide them with data necessary for business analytics. Additionally, thanks to innovative applications on the Cloud platform, personal adaptation to the individual needs of users is made. All of this has also affected the emergence of Cloud-based marketing, which implies the activity of organizations focused on the digital delivery of products and services tailored to users’ individual needs. This paper analyzes the concept of Cloud marketing and defines Cloud marketing platforms that contribute to the optimization of marketing strategies, and the increase in return on investment.

This paper examines the growing issue of money laundering through cryptocurrencies on a global scale. Criminals use digital assets to launder illicitly obtained funds, converting them into cryptocurrencies to obscure the origins of the money. Unlike traditional financial systems, decentralized finance (DeFi) platforms lack mechanisms to freeze or block funds from suspicious sources, presenting a unique challenge for law enforcement. However, the blockchain underlying cryptocurrencies allows for the tracking of transactions across DeFi protocols, making it possible to trace asset movement, albeit with difficulty due to complex methods criminals use to mix and transfer funds across multiple wallets. The study employs official data from financial institutions between 2019 and 2023, using time-series analysis to forecast money laundering trends under both optimistic and pessimistic scenarios. The paper concludes by highlighting the ongoing efforts by regulatory bodies to strengthen measures aimed at preventing cryptocurrency-related money laundering.

In order to draw adequate conclusions, the data used in the paper are official data from financial institutions relevant to money laundering. The time series used in the paper includes data related to the period from 2016 to 2023 and the forecast model based on optimistic and pessimistic scenarios is constructed.

There has been a notable surge in scholarly interest in public-private partnerships (PPP), their forms, models and role in the development of social infrastructure. The growing body of research on PPPs makes bibliometric analysis in this area a pertinent task. This study focuses on the literature on PPPs published between 2000 and 2021 and indexed by Scopus, Google Scholar, and Crossref. The study examines the evolution and structure of publication activity and trends in co-authorship as well as reciprocal citation relationships between articles. The top cited publications, authors and journals are identified. We have also conducted a semantic analysis of publication titles and keyword co-occurrence relationships, building a co-occurrence map in VOSviewer software. These research results can be of interest to scholars and practitioners in the field of public-private partnerships.